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Red-Teaming LLMs with NVIDIA Garak
red-teaming-llms-with-garak
mukul975/Anthropic-Cybersecurity-Skills
339
This skill utilizes NVIDIA's open-source garak framework to conduct comprehensive red-teaming assessments on Large Language Models (LLMs). It tests for critical vulnerabilities such as prompt injection, jailbreaks, data leakage, and toxic content generation by sending thousands of adversarial probes. Ideal for pre-deployment security validation, API guardrail testing, and generating defensible evidence for AI risk assessments.
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Probing Prompt Injection in RAG Systems
testing-prompt-injection-in-rag-pipelines
mukul975/Anthropic-Cybersecurity-Skills
361
A comprehensive red-teaming skill for assessing the security posture of Retrieval-Augmented Generation (RAG) pipelines. It systematically probes two critical injection surfaces: poisoned retrieved context (indirect prompt injection) and embedding manipulation. Use this skill to validate retrieval guardrails, ensure data leak prevention, and demonstrate vulnerabilities in LLM-powered knowledge assistants.
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